Examining the Perceptions Among Undergraduate Nursing Students Using Virtual Reality in a Community Course: A Mixed-Methods Explanatory Study.

PURPOSE: This study investigated undergraduate nursing students' perceptions of integrating virtual reality (VR) technology into a community nursing course, specifically home and environmental patient safety assessments. DESIGN: This study used a mixed-methods approach with an explanatory design. METHODS: Participants were recruited from a community health course. The students engaged in a VR simulation involving home visits using the vizHome platform. Quantitative and qualitative data were gathered using the Technology Acceptance Model (TAM) and the System Usability Scale (SUS). Semi-structured interviews were conducted. Quantitative data were collected through Qualtrics and secure Zoom connections for the interviews. The data were analyzed with SPSS and MAXQDA. FINDINGS: The results indicated that participants perceived VR as valuable and easy to use for learning home assessment skills. The System Usability Scale (SUS) score revealed room for improvement. Technical limitations were identified as challenges that must be addressed to enhance the user experience. CONCLUSION: Participants acknowledged VR's potential to supplement traditional learning methods, providing safe and realistic exposure to diverse home environments. While VR was seen as beneficial, it was not considered a replacement for actual home visits in community nursing education. CLINICAL EVIDENCE: This study provided clinical teaching evidence on the usability and student perceptions of VR in community courses.

A GREEDY METHOD FOR RECONSTRUCTING POLYCRYSTALS FROM THREE-DIMENSIONAL X-RAY DIFFRACTION DATA.

An iterative search method is proposed for obtaining orientation maps inside polycrystals from three-dimensional X-ray diffraction (3DXRD) data. In each step, detector pixel intensities are calculated by a forward model based on the current estimate of the orientation map. The pixel at which the experimentally measured value most exceeds the simulated one is identified. This difference can only be reduced by changing the current estimate at a location from a relatively small subset of all possible locations in the estimate and, at each such location, an increase at the identified pixel can only be achieved by changing the orientation in only a few possible ways. The method selects the location/orientation pair indicated as best by a function that measures data consistency combined with prior information on orientation maps. The superiority of the method to a previously published forward projection Monte Carlo optimization is demonstrated on simulated data.